Adaptive computing on the grid using AppLeS

TLDR

Computational grids aggregate vast bandwidth, compute, memory, and storage resources, yet harnessing this potential in dynamic, heterogeneous environments requires adaptive strategies. AppLeS supplies a methodology, application software, and runtime environments that enable adaptive scheduling and deployment of applications across multi‑user, heterogeneous grid infrastructures. The project demonstrates that AppLeS facilitates adaptive scheduling, leading to improved application performance in dynamic grid settings.

Abstract

Ensembles of distributed, heterogeneous resources, also known as computational grids, have emerged as critical platforms for high-performance and resource-intensive applications. Such platforms provide the potential for applications to aggregate enormous bandwidth, computational power, memory, secondary storage, and other resources during a single execution. However, achieving this performance potential in dynamic, heterogeneous environments is challenging. Recent experience with distributed applications indicates that adaptivity is fundamental to achieving application performance in dynamic grid environments. The AppLeS (Application Level Scheduling) project provides a methodology, application software, and software environments for adaptively scheduling and deploying applications in heterogeneous, multiuser grid environments. We discuss the AppLeS project and outline our findings.